AI Job Risk in Australia

Average generative-AI exposure of the workforce

0.315

ILO score (0–1). Rank 10 of 20 countries.

People in employment, 2025

14,170,000

ILO modelled estimate

What people in Australia work as

Share of employment in each ISCO-08 major occupation group, and the group's average generative-AI exposure (ILO score, 0–1). The country figure above is the employment-weighted average of the exposure column.

Occupation group	Share of employment	Exposure (ILO, 0–1)
Professionals	24.9%	0.39
Service and sales workers	16.6%	0.26
Technicians and associate professionals	13.4%	0.35
Managers	11.6%	0.36
Craft and related trades workers	9.6%	0.17
Skilled agricultural workers and elementary occupations	9.4%	0.15
Clerical support workers	8.7%	0.53
Plant and machine operators, and assemblers	5.9%	0.20

Method: each country's employment by ISCO-08 major occupation group (ILOSTAT, ILO modelled estimates) multiplied by the average ILO exposure score of the occupations in that group (ILO Working Paper 140), then added up. The ILO publishes skilled agricultural workers and elementary occupations as one group and leaves out the armed forces. The figure uses the ILO's 0–1 scale, not the 0–100 occupation index used elsewhere on this site, and it treats an occupation as equally exposed in every country.

How to read this page in practice

The notes below explain how to read the country figure, what kind of occupation mix raises or lowers it, and what this comparison can and cannot tell you.

How to Read This Country

Australia is best read by separating city-based knowledge and service work from resource extraction and care work spread across a huge, sparsely populated landmass. Banking, insurance, and professional services concentrated in state capitals sit in the exposed layer, since this work is standardized, digitized, and unconstrained by distance. Mining operations, agriculture, and the fast-growing aged-care and disability-support sectors sit in the durable layer, where site-based safety obligations, seasonal and environmental variability, and direct personal care keep human labor central regardless of how advanced supporting software becomes.

What drives the figure

Employment concentrates in financial and professional services in the major capitals, a mining and resources sector that drives exports but employs a smaller, geographically remote workforce, and a large and expanding health and aged-care sector responding to an ageing population. AI pressure is strongest in mortgage processing, insurance claims, superannuation administration, and back-office banking. It moves more slowly through fly-in fly-out mining operations, farming tied to land and weather, and direct aged-care and disability support work, where an ageing population is increasing demand for hands-on human care faster than automation can substitute for it.

What Holds Up Better

The most durable roles combine site-based physical work with rising demand from demographic change: mining technicians and heavy-equipment operators, agricultural workers tied to seasonal and regional conditions, and aged-care and disability-support workers whose numbers need to grow simply because Australia's population is getting older. The sheer distance separating major cities from resource regions also means centrally designed automation is harder to roll out uniformly across the country, and remote and fly-in fly-out work schedules keep a premium on people who can be physically present on site.

What This Page Does Not Claim

A national score blends a handful of dense coastal service economies with vast inland mining and agricultural regions, plus a care sector expanding for demographic reasons unrelated to AI. It cannot show how much of the measured exposure sits in Sydney and Melbourne offices versus remote mine sites and farms hundreds of kilometers away. Read the score alongside geographic concentration and the demand pressure coming from an ageing population, not as a single uniform trend across such a large country.

Jobs Most At Risk from AI

This table is a current snapshot of the jobs that appear on the higher-risk side within this country profile. It is useful as a directional comparison, not as a permanent national ranking. Both lists only include jobs in the three occupation groups that employ the most people in Australia, ordered by exposure index.

Rank	Job	Occupation group	Generative-AI exposure
1	Interpreter	Professionals	98
2	Translator	Professionals	98
3	Web Developer	Professionals	97
4	Technical Writer	Professionals	96
5	Programmer	Professionals	96
6	Content Writer	Professionals	95
7	Copywriter	Professionals	95
8	Data Analyst	Professionals	95
9	Data Scientist	Professionals	95
10	Software Tester	Professionals	95
11	Advertising Specialist	Professionals	94
12	Market Research Analyst	Professionals	94
13	Marketing Specialist	Professionals	94
14	SEO Specialist	Professionals	94
15	Social Media Manager	Professionals	94
16	IT Support Specialist	Technicians and associate professionals	94
17	Editor	Professionals	94
18	Sales Representative	Technicians and associate professionals	93
19	Telemarketer	Service and sales workers	93
20	Journalist	Professionals	93

Jobs Safest from AI

This table shows the jobs that currently appear on the lower-risk side within this country profile. Read it as a structural comparison of work, not as a guarantee that these roles will stay unchanged.

Rank	Job	Occupation group	Generative-AI exposure
1	Firefighter	Service and sales workers	25
2	Ship Engineer	Technicians and associate professionals	27
3	Water Treatment Operator	Technicians and associate professionals	27
4	Veterinary Assistant	Technicians and associate professionals	28
5	Paramedic	Technicians and associate professionals	32
6	Dentist	Professionals	33
7	Laboratory Technician	Technicians and associate professionals	37
8	Pilot	Technicians and associate professionals	39
9	Power Plant Operator	Technicians and associate professionals	39
10	Security Guard	Service and sales workers	39
11	Fitness Trainer	Technicians and associate professionals	39
12	Barista	Service and sales workers	39
13	Surgeon	Professionals	39
14	Sound Engineer	Technicians and associate professionals	41
15	Ship Captain	Technicians and associate professionals	42
16	Bartender	Service and sales workers	43
17	Chef	Technicians and associate professionals	44
18	Cook	Service and sales workers	44
19	Medical Assistant	Technicians and associate professionals	46
20	Veterinarian	Professionals	47

Sources

Exposure index calculated by ai-job-risk.net from the datasets below (data as of October 15, 2026). US labour figures are from the BLS, unchanged.

The publishers did not prepare, review or endorse this site. Full citations, licences and method

Frequently asked questions

Q.Which jobs are most at risk from AI in Australia?

Most exposed: Interpreter, Translator, Web Developer. Employment concentrates in financial and professional services in the major capitals, a mining and resources sector that drives exports but employs a smaller, geographically remote workforce, and a large and expanding health and aged-care sector responding to an ageing population. AI pressure is strongest in mortgage processing, insurance claims, superannuation administration, and back-office banking.

Q.Which jobs are safest from AI in Australia?

Least exposed: Firefighter, Ship Engineer, Water Treatment Operator. The most durable roles combine site-based physical work with rising demand from demographic change: mining technicians and heavy-equipment operators, agricultural workers tied to seasonal and regional conditions, and aged-care and disability-support workers whose numbers need to grow simply because Australia's population is getting older. The sheer distance separating major cities from resource regions also means centrally designed automation is harder to roll out uniformly across the country, and remote and fly-in fly-out work schedules keep a premium on people who can be physically present on site.

Q.How exposed is Australia to AI automation?

Australia is best read by separating city-based knowledge and service work from resource extraction and care work spread across a huge, sparsely populated landmass. Banking, insurance, and professional services concentrated in state capitals sit in the exposed layer, since this work is standardized, digitized, and unconstrained by distance. Mining operations, agriculture, and the fast-growing aged-care and disability-support sectors sit in the durable layer, where site-based safety obligations, seasonal and environmental variability, and direct personal care keep human labor central regardless of how advanced supporting software becomes.

Q.Does high exposure mean jobs will disappear in Australia?

A national score blends a handful of dense coastal service economies with vast inland mining and agricultural regions, plus a care sector expanding for demographic reasons unrelated to AI. It cannot show how much of the measured exposure sits in Sydney and Melbourne offices versus remote mine sites and farms hundreds of kilometers away. Read the score alongside geographic concentration and the demand pressure coming from an ageing population, not as a single uniform trend across such a large country.